Financial frauds are increasing day by day over the world the financial frauds has been increased by 56% since last 10 years. To reduce the frauds and to avoid corruption we have built this application.

What it does

It predicts whether the person is eligible for loan or not based on financial history. We have used ML algorithms like

  1. Artificial Neural Networks
  2. K Nearest Neighbors
  3. Decision Trees
  4. AdaBoost
  5. Random Forest
  6. Random Forest + AdaBoost

With best results from Random Forest and Adaboost we have predicted. Tells whether loan will be approved or not.

How we built it

We built using Flask framework, python libraries and machine learning algorithms.

Challenges we ran into

Deploying the framework, running different ml algorithms.

Accomplishments that we're proud of

Successfully completed the prediction part with 65% accuracy

What we learned

Teamwork, brushing up concepts.

What's next for Credit Baba

Next we will deploy it and add db to it

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